Results 41 to 50 of about 1,044,082 (362)
On the Computability of Conditional Probability [PDF]
Journal of the ACM, 2010 As inductive inference and machine-learning methods in computer science see continued success, researchers are aiming to describe ever more complex probabilistic models and inference algorithms.
N. Ackerman +2 more
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Geometric branching reproduction Markov processes
Modern Stochastics: Theory and Applications, 2020 We present a model of a continuous-time Markov branching process with the infinitesimal generating function defined by the geometric probability distribution.
Assen Tchorbadjieff, Penka Mayster
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Multiscale Data-Driven Energy Estimation and Generation
Physical Review X, 2023 We develop a multiscale approach to estimate high-dimensional probability distributions. Our approach applies to cases in which the energy function (or Hamiltonian) is not known from the start.
Tanguy Marchand +3 more
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Corrigendum: Characterizing a Joint Probability Distribution by Conditionals [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1999 With regard to the theorem in the paper, the second part is, in general, false, and the proof, given in Section 4.2, is in error. Dr K. W. Ng and Professor A. P. Dawid have pointed out the following simple counter-example for two binary random variables x,, x2: P(0, 0) = 0.3, P(0, 1) = 0.2, P(1, 0) = 0.2 and P(1, 1) = 0.3.
A. Gelman, T. P. Speed
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Energy Reports, 2023 The intermittency of distributed renewable energy resources (DRERs) and the fluctuation of load demand make the supply–demand scenario of active distribution systems significantly different from that of traditional radial distribution systems.
Yuxin Ye +5 more
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Statistics in Medicine, 2009 The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates.
P. Austin
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High-order Vector Markov Chain with Partial Connections in Data Analysis
Austrian Journal of Statistics, 2017 A new mathematical model for discrete time series is proposed: homogenous vector Markov chain of the order s with partial connections. Conditional probability distribution for this model is determined only by a few components of previous vector states ...
Yuriy Kharin, Michail Maltsew
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Finding Association Rules by Direct Estimation of Likelihood Ratios
, 2017 In this paper, we propose a cost function that corresponds to the mean square errors between estimated values and true values of conditional probability in a discrete distribution. We then obtain the values that minimize the cost function.
Kawakami, Kento +4 more
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Convergence results for conditional expectations [PDF]
, 2005 Let E,F be two Polish spaces and [Xn,Yn],[X,Y] random variables with values in E×F (not necessarily defined on the same probability space). We show some conditions which are sufficient in order to assure that, for each bounded continuous function f on E ...
Crimaldi, Irene, Pratelli, Luca
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Simplified amino acid alphabets based on deviation of conditional probability from random background. [PDF]
Physical review. E, Statistical, nonlinear, and soft matter physics, 2002 The primitive data for deducing the Miyazawa-Jernigan contact energy or blocks substitution matrix (BLOSUM) consists of pair frequency counts. Each amino acid corresponds to a conditional probability distribution.
Xin Liu, Di Liu, Jinyao Qi, Weinan Zheng
semanticscholar +1 more source